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Record W1985142242 · doi:10.1097/mlr.0b013e3181649412

Addressing the Unit of Analysis in Medical Care Studies

2008· review· en· W1985142242 on OpenAlexaff
Aaron W. Calhoun, Gordon Guyatt, Michael D. Cabana, Downing Lu, David A. Turner, Stacey L. Valentine, Adrienne G. Randolph

Bibliographic record

VenueMedical Care · 2008
Typereview
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsMcMaster University
Fundersnot available
KeywordsUnit (ring theory)MedicineError analysisIntervention (counseling)Family medicinePsychologyMathematicsNursing

Abstract

fetched live from OpenAlex

OBJECTIVE: We assessed the frequency that patients are incorrectly used as the unit of analysis among studies of physicians' patient care behavior in articles published in high impact journals. METHODS: We surveyed 30 high-impact journals across 6 medical fields for articles susceptible to unit of analysis errors published from 1994 to 2005. Three reviewers independently abstracted articles using previously published criteria to determine the presence of analytic errors. RESULTS: One hundred fourteen susceptible articles were found published in 15 journals, 4 journals published the majority (71 of 114 or 62.3%) of studies, 40 were intervention studies, and 74 were noninterventional studies. The unit of analysis error was present in 19 (48%) of the intervention studies and 31 (42%) of the noninterventional studies (overall error rate 44%). The frequency of the error decreased between 1994-1999 (N = 38; 65% error) and 2000-2005 (N = 76; 33% error) (P = 0.001). CONCLUSIONS: Although the frequency of the error in published studies is decreasing, further improvement remains desirable.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.058
metaresearch head score (Gemma)0.184
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad), Open science, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.974
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0580.184
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0210.009
Bibliometrics0.0010.010
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0060.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.937
GPT teacher head0.672
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations16
Published2008
Admission routes1
Has abstractyes

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